6 papers
Unsupervised patch-based dynamic MRI reconstruction using learnable tensor function with implicit neural representation
Yuanyuan Liu, Yuanbiao Yang, Jing Cheng +8
Dynamic MRI suffers from limited spatiotemporal resolution due to long acquisition times. Undersampling k-space accelerates imaging but makes accurate reconstruction challenging. S…
Guided MRI Reconstruction via Schrödinger Bridge
Yue Wang, Yuanbiao Yang, Zhuo-xu Cui +5
Magnetic Resonance Imaging (MRI) is an inherently multi-contrast modality, where cross-contrast priors can be exploited to improve image reconstruction from undersampled data. Rece…
Accurate myocardial T1 mapping at 5T using an improved MOLLI method: A validation study
Linqi Ge, Yinuo Zhao, Yubo Guo +7
Background: Accurate myocardial T1 mapping at 5T remains a technical challenge due to field inhomogeneity and prolonged T1 values. The aim of this study is to develop an accurate a…
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
The reconstruction of visual information from brain activity fosters interdisciplinary integration between neuroscience and computer vision. However, existing methods still face ch…
Myocardial T1 mapping at 5T using multi-inversion recovery real-time spoiled GRE
Linqi Ge, Yihang Zhang, Huibin Zhu +6
Objective: To develop an accurate myocardial T1 mapping technique at 5T using Look-Locker-based multiple inversion-recovery with the real-time spoiled gradient echo (GRE) acquisiti…
HAVIR: HierArchical Vision to Image Reconstruction using CLIP-Guided Versatile Diffusion
Shiyi Zhang, Dong Liang, Hairong Zheng +1
Reconstructing visual information from brain activity bridges the gap between neuroscience and computer vision. Even though progress has been made in decoding images from fMRI usin…